TW201909303A - Hybrid detection system for efficient window processing - Google Patents

Abstract

An inspection system includes a controller communicatively coupled to a physical inspection device (PID), a virtual inspection device (VID) configured to analyze stored PID data, and a defect verification device (DVD). The controller may receive a pattern layout of a sample including multiple patterns fabricated with selected lithography configurations defining a process window, receive locations of PID-identified defects identified through analysis of the sample with the PID, wherein the PID-identified defects are verified by the DVD, remove one or more lithography configurations associated with the locations of the PID-identified defects from the process window, iteratively refine the process window by removing one or more lithography configurations associated with VID-identified defects identified through analysis of selected portions of stored PID data with the VID, and provide, as an output, the process window when a selected end condition is met.

Description

Hybrid detection system for efficient processing of window exploration

The present invention relates generally to detection systems, and more particularly, to hybrid detection systems for processing window determinations.

A processing window of a semiconductor process (for example, a lithographic processing step) represents a parameter range, and a pattern of interest for the parameter range can be reliably manufactured on a sample without substantial defects. Accurate determination of the processing window is critical to providing both accuracy and throughput during manufacturing. A processing window that is too restrictive can place an unnecessary burden on a control system that is used to control one of the relevant parameters that may approach the theoretical limit. In addition, an overly broad processing window can lead to defective manufacturing, which can negatively affect device performance or cause device failure. However, processing window qualifications can often be a time-consuming and expensive procedure. Therefore, it may be necessary to provide systems and methods for advanced process window qualification verification.

A detection system according to one or more illustrative embodiments of the invention is disclosed. In an illustrative embodiment, the system includes a controller communicatively coupled to a physical detection device (PID), a virtual detection device (VID) configured to analyze stored PID data, and a Defect Verification Device (DVD). According to one or more illustrative embodiments of the present invention, the controller receives a pattern layout including a sample of a plurality of patterns manufactured with a selected lithographic configuration defining a processing window. According to one or more illustrative embodiments of the invention, the pattern layout relates the positions of the plurality of patterns on the sample to the lithographic configuration of the processing window. According to one or more illustrative embodiments of the present invention, the controller receives a PID identifying the location of the defect, wherein the PID identifying defect is verified by the DVD. According to one or more illustrative embodiments of the invention, the controller removes from the processing window one or more lithographic configurations associated with the locations of the PID identification defects. According to one or more illustrative embodiments of the present invention, the controller is configured by removing one or more lithographic configurations associated with a VID identification defect identified by analyzing selected portions of the stored PID data using the VID The processing window is repeatedly improved. According to one or more illustrative embodiments of the present invention, the controller provides the processing window as an output when a selected end condition is satisfied.

A detection system according to one or more illustrative embodiments of the invention is disclosed. In an illustrative embodiment, the system includes a physical detection device (PID). In another illustrative embodiment, the system includes a virtual detection device (VID) configured to analyze stored PID data. In another illustrative embodiment, the system includes a defect verification device (DVD). In another illustrative embodiment, the system includes a controller communicatively coupled to the PID, the VID, and the DVD. According to one or more illustrative embodiments of the present invention, the controller receives a pattern layout including a sample of a plurality of patterns manufactured with a selected lithographic configuration defining a processing window. According to one or more illustrative embodiments of the invention, the pattern layout relates the positions of the plurality of patterns on the sample to the lithographic configuration of the processing window. According to one or more illustrative embodiments of the present invention, the controller receives a location of a PID identification defect identified by analyzing the sample with the PID, wherein the PID identification defects are verified by the DVD. According to one or more illustrative embodiments of the invention, the controller removes from the processing window one or more lithographic configurations associated with the locations of the PID identification defects. According to one or more illustrative embodiments of the present invention, the controller is configured by removing one or more lithographic configurations associated with a VID identification defect identified by analyzing selected portions of the stored PID data using the VID The processing window is repeatedly improved. According to one or more illustrative embodiments of the present invention, the controller provides the processing window as an output when a selected end condition is satisfied.

A detection method according to one or more illustrative embodiments of the invention is disclosed. In an illustrative embodiment, the method includes receiving a pattern layout including a sample of one of a plurality of patterns made with a selected lithographic configuration defining a processing window. According to one or more illustrative embodiments of the invention, the pattern layout relates the positions of the plurality of patterns on the sample to the lithographic configuration of the processing window. According to one or more illustrative embodiments of the invention, the method includes detecting the sample with a physical detection device (PID) to generate a PID identification defect. According to one or more illustrative embodiments of the invention, the method includes verifying the PID identification defects with a defect verification device (DVD). According to one or more illustrative embodiments of the invention, the method includes removing from the processing window one or more lithographic configurations associated with the locations of the PID identification defects. According to one or more illustrative embodiments of the present invention, the method includes by removing one or more lithographic configurations associated with a VID identification defect identified by analyzing selected portions of the stored PID data with the VID. The processing window is repeatedly improved. According to one or more illustrative embodiments of the invention, the method includes providing the processing window as an output when a selected end condition is satisfied.

It should be understood that both the foregoing summary and the following detailed description are exemplary and explanatory only and are not necessarily restrictive of the invention as claimed. The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments of the invention and together with the summary serve to explain the principles of the invention.

Cross-reference to related applications

This application claims to designate Brian Duffy as the inventor under 35 USC § 119 (e). The application titled HYBRID INSPECTOR FOR EFFICIENT NON-CONFORMANCE DISCOVERY was filed July 25, 2017. Rights, the entire text of which is incorporated herein by reference.

Reference will now be made in detail to the disclosed subject matter illustrated in the accompanying drawings. The invention has been shown and described with particular reference to certain embodiments and their specific features. The embodiments illustrated herein are to be regarded as illustrative rather than restrictive. Those of ordinary skill should readily understand that various changes and modifications in form and detail can be made without departing from the spirit and scope of the invention.

Embodiments of the present invention relate to a hybrid detection system for efficiently determining a processing window for a process. A hybrid inspection system may include (but need not include): a physical inspection device (PID) (e.g., an optical inspection system, an electron-beam / e-beam inspection system, or the like), suitable for analysis A virtual inspection device (VID) of the stored PID data, a defect verification device (DVD) for verifying defects identified by the PID and / or the VID, and a controller. Additional embodiments of the present invention are related to improvement by repeatedly removing self-processing windows from lithographic configurations (e.g., specific program parameter sets) that cause manufacturing defects on at least one pattern of interest (POI) within a selected evaluation criterion. Candidate processing window.

A processing window of a process may represent a lithographic configuration range (eg, conditions, parameters, or the like) suitable for manufacturing a selected set of patterns on a wafer within a desired specification. For example, a processing window may define a limit on defocus associated with the position of the sample (eg, the focal position of the sample) along the optical axis of the lithography tool. By way of another example, a processing window may define a limitation on the energy dose (e.g., the exposure of the sample) incident on the sample from the illumination source. In addition, the effects of changes in a number of program parameters on one or more of the printed features may be dependent. In this regard, a processing window may include a multi-dimensional representation of a plurality of program parameters (e.g., a focus exposure matrix (FEM) or the like) defining an acceptable range of program parameters of interest. Therefore, accurate monitoring of process parameters, such as, but not limited to, the focal position of the sample and the energy dose incident on the sample from an illumination source, can facilitate the performance of the lithographic tool according to the desired specifications.

An additional embodiment of the present invention pertains to performing a process window qualification test (PWQ) by analyzing a test sample (e.g., a design of experiment (DOE) sample, a modulation sample, or the like) on the test sample. A lithographic configuration representing a systematic variation of a candidate processing window makes various POIs. In this regard, one or more POIs for which the lithographic configuration is defective (e.g., for a specific value of a FEM or the like) may be removed from the candidate processing window. Thus, a processing window may be generated for each POI and / or for a whole set of POIs related to a particular manufacturing step.

It is often necessary to characterize as accurately and / or practically as possible a processing window for fabricating a pattern of interest (POI) in a process. For example, related procedure parameters (eg, the focus of the sample, the dose incident on the sample, or the like) can be controlled using a control system to remain within the processing window. Therefore, the accurate characterization of the processing window can promote the reliable performance of the lithography system with minimal manufacturing errors and high throughput.

There may further be a need to efficiently determine processing windows before production to simplify pre-production procedures. It should be recognized in this article that processing window qualification is a time-consuming process that can take several days to complete. A typical PWQ analysis can usually be performed with a high-resolution detection system such as, but not limited to, a SEM capable of imaging a POI on a test sample. However, detection using a single system with sufficient resolution to fully image the POI is often attributed to impractical and / or undesirable requirements that require significant time and / or computational resources.

Therefore, some inspection systems can identify possible defect sites through a two-pass process by using a higher throughput, usually lower resolution inspection system and then using a high resolution inspection system (verification system) (such as a SEM) verifies only the identified possible defect sites to determine the processing window. In addition, the double-pass process may need to be repeated several times to achieve the accuracy required by one of the PWQ levels. However, the transfer of specimens between different detection systems can introduce significant delays that limit the throughput of the system and the risk of sample contamination, which negatively affects the accuracy and / or efficiency of the processing window determination. To mitigate these negative effects of sample transfer between multiple detection systems, each iteration may include analyzing and subsequently verifying a relatively large portion of the sample to ensure that sufficient data is collected to improve the processing window. However, this procedure is inefficient and can lead to the collection of large amounts of unnecessary data.

An additional embodiment of the present invention relates to determining a processing window with a hybrid detection system by detecting a test sample with a PID, storing the PID data, and repeatedly improving the processing window by analyzing the stored PID data with a VID calibration. Hybrid detection systems are generally described in U.S. Patent Publication No. 2017/0194126, entitled "Hybrid Inspectors" and published on July 26, 2017, the entirety of which is incorporated herein. Each analysis iteratively targets a portion of the sample that may contain defects and therefore may lead to a reduction in the processing window. In addition, samples need only be transferred from PID to DVD once, which can facilitate highly accurate and efficient processing window determination. For example, an entire sample (or a relevant portion of the sample) may be initially analyzed using PID and then transferred to a DVD. Once in the SEM, the portion of the sample that may contain defects can be identified, the relevant portion of the stored PID data can be analyzed with VID to identify patterns with possible defects, and the possible defects can be verified with SEM. This procedure can be repeated any number of times without moving the sample. In addition, various steps can be performed in parallel to further facilitate efficient detection of the processing window.

An additional embodiment of the present invention relates to correlating a possible defect with a specific pattern on a sample based on a known pattern layout of the sample. In this regard, possible defects identified by PID or VID may be related to known pattern elements on the sample. Further embodiments of the present invention relate to assigning a figure of merit (FOM) to various POIs based on the number of defects associated with the POI and the scope of the lithographic configuration associated with the defects. For example, the situation may be that certain POIs can be relatively robust and can be manufactured flawlessly through a wide range of lithographic configurations (e.g., with a large processing window), while other POIs can be less robust and can be passed through a relatively small A range of lithographic configurations (e.g., with a small processing window) are manufactured without defects. In this regard, FOM can be used to identify relatively weak patterns. In addition, these relatively weak patterns can be preferentially targeted for analysis with VID and SEM to improve the processing window efficiently.

Additional embodiments of the present invention are related to the location of the POI and the specific analysis area of the PID (e.g., a scanning band or sub-scanning band of a scanning tool, an image of an imaging tool, or the like) manufactured using various lithographic configurations, and / Or related to a specific field of view of the DVD. In this regard, specific patterns and associated lithographic configurations used to make those patterns may be indexed to a known measurement area of the PID and / or the field of view of the DVD. Further embodiments of the present invention pertain to assigning a learning potential to each of the individual scan bands or sub-scan bands and / or DVDs of the PID based on the merit for the included pattern (e.g., indicating the robustness of the pattern to manufacturing defects). Field of view. Therefore, the processing window can be efficiently improved by prioritizing the scanning bands and / or fields of view that are expected to contain a relatively high defect probability.

An additional embodiment of the present invention is to update the figure of merit and / or learning potential after each iteration of analysis using VID and verification using DVD. Therefore, the repeated results of each analysis can be used to affect the determination of the next part of the sample most likely to contain defects for efficient improvement of the processing window. A further embodiment of the present invention relates to the use of mechanical learning algorithms (eg, neural networks and the like) to identify portions of samples analyzed during each iteration based on the results of previous iterations.

An additional embodiment of the present invention is related to the improvement of terminating the processing window when a selected end condition is satisfied. For example, the improvement of the processing window may be terminated when the learning potential for all scan bands drops below a selected threshold. By way of another example, the improvement of the processing window may be terminated after a selected number of iterations of analysis using VID and verification using DVD. With a further example, the improvement of the processing window can be terminated after a selected time frame.

A hybrid inspection system 100 can therefore provide efficient verification of the process window by repeatedly improving the processing window by analyzing the stored PID data with a VID calibration and verifying with a DVD. For example, the hybrid inspection system 100 may prioritize the portion of a test sample with a large number and / or diversity of POIs that are identified as likely to contain defects and thus maximize the impact or learning rate of each iteration. In addition, once a defect is identified for a particular POI when it is manufactured using a particular lithographic condition based on a selected evaluation criterion, it is not necessary to re-analyze any duplicate instances of that particular POI manufactured under that particular lithographic condition (e.g. On the same die or on different die throughout the sample). This can substantially limit the surface area of the sample that must be analyzed by a time-consuming DVD and can additionally limit unnecessary and redundant measurements.

As used throughout the present invention, the term "sample" generally refers to a substrate (eg, a wafer or the like) formed from a semiconductor or non-semiconductor material. For example, a semiconductor or non-semiconductor material may include, but is not limited to, single crystal silicon, gallium arsenide, and indium phosphide. A sample may contain one or more layers. For example, these layers may include, but are not limited to, a photoresist, a dielectric material, a conductive material, and a semi-conductive material. Many different types of these layers are known in the art, and the term sample as used herein is intended to encompass a sample on which all types of these layers can be formed. One or more layers formed on the sample can be patterned or unpatterned. For example, a specimen may include a plurality of grains, each grain having repeatable patterning features. The formation and processing of these material layers can ultimately lead to a finished device. Many different types of devices may be formed on a sample, and the term sample as used herein is intended to cover one of the types of devices on which any type of device known in the art is manufactured. For the purposes of the present invention, the terms sample and wafer should be interpreted interchangeably.

FIG. 1A is a conceptual diagram of a hybrid detection system 100 according to one or more embodiments of the present invention.

In one embodiment, the hybrid inspection system 100 includes a physical inspection device (PID) 102 for detecting possible manufacturing defects on a physical sample including a manufactured structure. For example, the PID 102 may include, but is not limited to, an optical detection device or an electron beam detection device. In this regard, the PID 102 may generate information indicating the manufactured structures on the test sample (e.g., one or more images of the manufactured structures). In addition, the PID 102 may store or otherwise provide the generated data for further analysis.

In another embodiment, the hybrid detection system 100 includes a virtual detection device (VID) 104 for analyzing data (eg, stored PID data) from the PID 102. VID 104 may operate in substantially the same manner as a PID 102, except that VID 104 may identify and / or classify possible defects by analyzing data from PID 102 rather than by analyzing a physical sample. In this regard, VID 104 can facilitate repeated analysis of the sample without the need for duplicate physical measurements of the same sample.

In another embodiment, the hybrid inspection system 100 includes a defect verification device (DVD) 106 for analyzing a physical sample to verify one of the possible defects identified by the PID 102 and / or the VID 104. For example, the DVD 106 may include, but is not limited to, a scanning electron microscope (SEM). In this regard, DVD 106 can provide sample analysis with a resolution that is relatively higher than PID 102, so that DVD 106 can identify defects with a higher accuracy than PID 102. Therefore, the DVD 106 may have (but does not need to have) a throughput that is relatively lower than one of the PID 102.

Therefore, the hybrid detection system 100 can dynamically balance the accuracy of the DVD 106 with the detection speed of the PID 102 and / or VID 104 to achieve a desired level of performance and throughput. In addition, the hybrid detection system 100 can perform repeated analysis of the calibration portion of the sample without the need for multiple sample transfers. For example, the PID 102 may provide a first pass defect identification analysis of one of the samples and may further provide output data suitable for subsequent analysis using the VID 104. Test samples can then be transferred to DVD 106 for verification of PID identification defects. Subsequent analysis and verification steps can then be performed sequentially or in parallel by VID 104 and DVD 106 without further transferring test samples. In addition, because the test samples remain in the DVD 106, each subsequent iteration may include analysis of small, calibrated portions of the samples that are expected to provide relevant information for efficiently improving the processing window.

In another embodiment, the hybrid detection system 100 includes a controller 108. In another embodiment, the controller 108 includes one or more processors 110 configured to execute program instructions maintained on a memory medium 112. In this regard, one or more of the processors 110 of the controller 108 may perform any of the various processing steps described throughout this disclosure.

One or more processors 110 of a controller 108 may include any processing element known in the art. In this sense, one or more processors 110 may include any microprocessor-type device configured to execute algorithms and / or instructions. In one embodiment, as described throughout the present invention, the one or more processors 110 may be a desktop computer, a mainframe computer system, a workstation, an imaging computer, a parallel processor, or configured to execute a configured It is composed of any other computer system (eg, a networked computer) that operates one of the programs of the hybrid detection system 100. It should be further appreciated that the term "processor" may be broadly defined to encompass any device having one or more processing elements that execute program instructions from a non-transitory memory medium 112.

The memory medium 112 may include any storage medium known in the art that is suitable for storing program instructions that can be executed by an associated processor or processors 110. For example, the memory 112 may include a non-transitory memory medium. By way of another example, the memory medium 112 may include (but is not limited to) a read-only memory, a random access memory, a magnetic or optical memory device (e.g., a magnetic disk), a magnetic tape, a solid state hard disk Disc players and the like. It should be further noted that the memory media 112 may be housed in a common controller enclosure with one or more processors 110. In one embodiment, the memory media 112 may be remotely located relative to the physical locations of the one or more processors 110 and the controller 108. For example, one or more processors 110 of the controller 108 may access a remote memory (eg, a server) that is accessible through a network (eg, the Internet, an intranet, and the like). Therefore, the above description should not be construed as limiting the invention but merely as an illustration.

The controller 108 may be configured to receive data from the PID 102, the VID 104, and / or the DVD 106. For example, the controller 108 may receive any combination of raw data, processed data (eg, test results), and / or partially processed data. In addition, the steps described throughout this disclosure may be performed by a single controller 108 or alternatively multiple controllers. In addition, the controller 108 may include one or more controllers housed in a common housing or multiple housings. In this manner, any controller or combination of controllers can be individually packaged as a module suitable for integration into the hybrid detection system 100. For example, the controller 108 may operate as a centralized processing platform for any one of the detection tools (e.g., PID 102, VID 104, and / or DVD 106) and may process received data (raw and / or partial processing) ) Implement one or more detection algorithms to determine the existence of defects on the sample. In another example, the controllers 108 may be distributed such that portions of the controllers 108 may be implemented in and / or housed in any combination of detection tools.

The controller 108 may further direct any of the detection tools to perform a detection step. For example, the controller 108 may provide a detection recipe for any of the PID 102, VID 104, and / or DVD 106, including (but not limited to) detection parameters (e.g., illumination intensity, detection gain, detection contrast, light spot size Or similar) and the position on the sample measured by PID 102 and / or DVD 106.

In one embodiment, the controller 108 may receive or generate one of the master recipes (eg, PID 102, VID 104, DVD 106, or the like) suitable for guiding the hybrid detection system 100. For example, the components of the hybrid detection system 100 may be queued as a job that includes a series of analyses or measurements to be performed. In addition, the components of the hybrid detection system 100 may respond to recipes including, but not limited to, configuration parameters or control instructions.

Referring now to FIGS. 1B to 1D, various components of the hybrid detection system 100 are described in more detail.

PID 102 may include any type of detection device known in the art to be suitable for detecting defects in a specimen. For example, the PID 102 may illuminate the specimen with an illumination beam and may further collect radiation emitted from the sample in response to the illumination beam. The illumination beam may include any type of illumination beam suitable for detecting a sample, such as (but not limited to): a beam (eg, a photon), an electron beam, or an ion beam. In addition, the radiation emitted from the sample may include photons, electrons, ions, neutral particles, or the like. Therefore, the PID 102 may include an optical detection device, an electron beam detection device, an ion beam detection device, or the like.

The PID 102 may further operate in an imaging mode or a non-imaging mode. For example, the PID 102 operating in an imaging mode may illuminate a portion of a sample larger than the system resolution and capture an image of the illuminated portion of the sample on a detector. The captured image may be any type of image known in the art, such as (but not limited to): a bright field image, a dark field image, a phase contrast image, or the like. In addition, the captured images can be stitched together (eg, by PID 102, by controller 108 or the like) to form a composite image of one of the samples. By way of another example, the PID 102 operating in a non-imaging mode can scan a focused beam across the sample and capture radiation from the sample and / or one or more detectors at one or more measurement angles and / or particle. The focused beam can be scanned through the sample by modifying the beam path (eg, using a galvanometer, a piezoelectric mirror, or the like) and / or by translating the sample through a focused volume of the focused beam.

FIG. 1B is a conceptual diagram of a PID 102 for scanning a focused optical illumination beam across a surface of a sample according to one or more embodiments of the present invention.

In one embodiment, the PID 102 includes an illumination source 114 for generating an illumination beam 116. The illumination beam 116 may include one or more selected light wavelengths, including, but not limited to, ultraviolet (UV) radiation, visible radiation, or infrared (IR) radiation.

The illumination source 114 may be any type of illumination source known in the art that is suitable for generating an optical illumination beam 116. In one embodiment, the illumination source 114 comprises a broadband plasma (BBP) illumination source. In this regard, the illumination beam 116 may include radiation emitted by a plasma. For example, a BBP illumination source 114 may include, but need not include, one or more pump sources (e.g., one or more lasers) that are configured to focus on a gas A volume, thereby causing energy to be absorbed by the gas in order to generate or maintain a plasma suitable for emitting radiation. In addition, at least a portion of the plasma radiation may be used as the illumination beam 116.

In another embodiment, the illumination source 114 may include one or more lasers. For example, the illumination source 114 may include any laser system known in the art that is capable of emitting radiation in the infrared, visible, or ultraviolet portions of the electromagnetic spectrum.

The illumination source 114 may further generate one of the illumination beams 116 having any temporal profile. For example, the illumination source 114 may generate a continuous illumination beam 116, a pulsed illumination beam 116, or a modulated illumination beam 116. In addition, the illumination beam 116 may be transmitted or guided from free space (eg, an optical fiber, a light pipe, or the like) from the illumination source 114 via free space.

In another embodiment, the illumination source 114 directs the illumination beam 116 to the sample 118 via an illumination path 120. The illumination path 120 may include one or more illumination path lenses 122 or additional optical components 124 adapted to modify and / or adjust the illumination beam 116. For example, one or more optical components 124 may include (but are not limited to): one or more polarizers, one or more filters, one or more beam splitters, one or more diffusers, one or more Homogenizers, one or more apodizers, or one or more beam shapers.

In another embodiment, the sample 118 is placed on the sample stage 126. The sample stage 126 may include any device suitable for positioning and / or scanning the sample 118 within the PID 102. For example, the sample stage 126 may include a linear translation stage, a rotary stage, a flip / tilt stage, or any combination thereof.

In another embodiment, the PID 102 includes one of the detectors 128 configured to capture radiation emitted from the sample 118 through a set of light paths 130. The light collecting path 130 may include, but is not limited to, one or more light collecting path lenses 132 for collecting radiation from the sample 118. For example, a detector 128 may receive radiation that is reflected or scattered from the sample 118 (eg, via specular reflection, diffuse reflection, and the like) via one or more light collecting path lenses 132. By way of another example, a detector 128 may receive radiation generated by the sample 118 (eg, a luminescence or the like associated with the absorption of the illumination beam 116). By way of another example, a detector 128 may receive radiation of one or more diffraction levels (e.g., order 0 diffraction, ± 1 order diffraction, ± 2 order diffraction, and the like) from the sample 118.

The detector 128 may include any type of detector known in the art that is suitable for measuring the illumination received from the sample 118. For example, a detector 128 may include (but is not limited to): a CCD detector, a TDI detector, a photomultiplier tube (PMT), a burst photodiode (APD), or the like. In another embodiment, a detector 128 may include a spectral detector suitable for identifying the wavelength of radiation emitted from the sample 118.

The light collection path 130 may further include any number of optical elements 134 to guide and / or modify the collected illumination from the sample 118, including (but not limited to) one or more light collection path lenses 132, one or more filters Light fixtures, one or more polarizers, or one or more beam stops.

FIG. 1C is a conceptual diagram of PID 102 for imaging and / or scanning a sample according to one or more embodiments of the present invention. In one embodiment, the detector 128 is positioned approximately normal to the surface of the sample 118. In another embodiment, the PID 102 includes a beam splitter 136 that is oriented such that an objective lens 138 can simultaneously direct the illumination beam 116 to the sample 118 and collect radiation emitted from the sample 118. In addition, the illumination path 120 and the light collection path 130 may share one or more additional elements (for example, an objective lens 138, an aperture, a filter, or the like).

FIG. 1D is a conceptual diagram of a PID 102 configured as a particle beam detection system according to one or more embodiments of the present invention. In one embodiment, the illumination source 114 includes a particle source (e.g., an electron beam source, an ion beam source, or the like) such that the illumination beam 116 includes a particle beam (e.g., an electron beam, a particle beam, or Similar). Illumination source 114 may include any particle source known in the art that is suitable for generating an illumination beam 116. For example, the illumination source 114 may include, but is not limited to, an electron gun or an ion gun. In another embodiment, the illumination source 114 is configured to provide a beam of particles having a tunable energy. For example, an illumination source 114 including an electron source may (but is not limited to) providing an accelerating voltage in a range of 0.1 kV to 30 kV. As another example, an illumination source 114 including an ion source may (but is not required to) provide an ion beam having an energy in the range of 1 keV to 50 keV.

In another embodiment, the illumination path 120 includes one or more particle focusing elements (eg, the illumination path lens 122, the light collection path lens 132, or the like). For example, the one or more particle focusing elements may include (but are not limited to): a single particle focusing element or one or more particle focusing elements forming a composite system. In another embodiment, the one or more particle focusing elements include an objective lens 138 configured to direct the illumination beam 116 to the sample 118. In addition, the one or more particle focusing elements may include any type of electronic lens known in the art, including (but not limited to): an electrostatic lens, a magnetic lens, a single potential lens, or a double potential lens. It should be noted herein that the description of one of the voltage contrast imaging detection systems as depicted in FIG. 1C and the associated description above are provided for illustration purposes only and should not be construed as limiting. For example, PID 102 may include any excitation source known in the art that is suitable for generating test data about specimen 118. In another embodiment, the PID 102 includes two or more particle beam sources (eg, an electron beam source or an ion beam source) for generating two or more particle beams. In a further embodiment, the PID 102 may include one or more components (eg, one or more electrodes) configured to apply one or more voltages to one or more locations of the sample 108. In this regard, the PID 102 can generate voltage contrast imaging data.

In another embodiment, the PID 102 includes one or more particle detectors 128 that image or otherwise detect particles emitted from the sample 118. In one embodiment, the detector 128 includes an electron collector (eg, a secondary electron collector, a backscattered electron detector, or the like). In another embodiment, the detector 128 includes a photon detector (e.g., a photodetector, an x-ray detector, coupled to a photoelectron) for detecting electrons and / or photons from the sample surface. (A flicker element or the like of a multiplier tube (PMT) detector).

The DVD 106 may include any type of detection or measurement system known in the art. In a general sense, the DVD 106 may include, but is not limited to, any of the detectors shown in FIGS. 1B-1D. The DVD 106 includes a detector having a resolution higher than that of the PID 102, so that the DVD 106 can verify that the PID data is manipulated by the PID 102 and / or by operating the PID data with an accuracy higher than that obtainable with the PID 102 Identify possible defects.

In one embodiment, the DVD 106 includes a SEM. In addition, the DVD 106 may include any type of SEM known in the art. For example, the DVD 106 may include a high magnification image configured to provide a possible defect and may therefore have a viewing SEM with a relatively small FOV. By way of a further example, the DVD 106 may include a detection SEM (eg, an electron beam detection system or the like) that is configured to provide a relatively large FOV. In this regard, a detection SEM can balance FOV and detection speed. By way of further example, the DVD 106 may include one SEM configured for measurement, such as (but not limited to) a critical dimension SEM (CD-SEM). For example, a CD-SEM may utilize a relatively low energy electron beam (such as, but not limited to, 1 keV or less) to reduce charging and thereby produce highly sensitive images with small defects.

In another embodiment, the DVD 106 can be dynamically switched between different measurement modes. For example, different types of defects and / or different POIs can benefit from different measurement modes. In this regard, the controller 108 may provide a recipe to the DVD 106 that provides a measurement configuration (eg, beam energy, sample deviation, or the like).

In another embodiment, the DVD 106 includes a plurality of SEM devices that can be selectively used within the hybrid detection system 100. For example, the DVD 106 may include a viewing SEM and a CD-SEM.

VID 104 may include any device or combination of devices suitable for analyzing data generated by PID 102 for defects. For example, VID 104 may include one or more controllers (e.g., one or more processors coupled to memory adapted to execute program instructions, as previously described herein). The virtual inspection system is generally described in U.S. Patent No. 9,222,895 entitled `` Generalized Virtual Inspector '' and granted rights on December 29, 2015 and entitled `` Virtual Inspection Systems for Process Window Characterization '' and on November 20, 2015 In published U.S. Patent Publication No. 2016/0150191, the entire contents of both are incorporated herein by reference.

In one embodiment, the VID 104 includes an independent computing device. For example, the VID 104 may include one or more processors coupled to memory and configured to execute program instructions for receiving and detecting data generated by the PID. The computing device of VID 104 is communicatively coupled to additional components of hybrid detection system 100 (such as, but not limited to, PID 102, a data storage unit (e.g., a database, a server, a memory unit, or the like) Or controller 108) to send or receive data, test results, or the like.

In another embodiment, the VID 104 is integrated into one or more components of the hybrid detection system 100. In this regard, the VID 104 need not include an independent computing system, but may be associated with the functionality of another component within the hybrid detection system 100. For example, the VID 104 may be integrated with the controller 108. By way of another example, VID 104 may be integrated with PID 102. In this regard, PID 102 may be configured to detect defects in a physical sample and may additionally be configured to detect stored data from a previous measurement of a sample.

FIG. 2 is a flowchart illustrating steps performed in a method 200 for determining a processing window according to one or more embodiments of the present invention. The applicant noted that the embodiments and enabling techniques previously described in the background of the hybrid detection system 100 herein should be interpreted as extending to the method 200. However, it should be further noted that the method 200 is not limited to the architecture of the hybrid detection system 100.

As previously described herein, a processing window may represent a lithographic configuration range (e.g., illumination dose during an exposure step, focus position of a sample during exposure, or the like) for which lithographic configuration range According to a selected defect tolerance, one or more patterns of interest can be manufactured without defects. Therefore, each pattern of interest may have a pattern-specific window. Furthermore, a given set of patterns of interest may have a processing window in which each pattern can be manufactured without defects.

This processing window may be initially defined as the lithographic configuration range used to generate the DOE samples. It is usually necessary to accurately determine the processing window (for example, the processing window for the set of patterns on the DOE sample) so that the parameters of the lithography system can be well controlled. Defining the processing window too narrow can place an unnecessary burden on the accuracy of the control system. In contrast, defining a processing window too broad can lead to manufacturing defects that exceed the selected defect tolerance.

It should be recognized herein that a particular number or type of defects in a given manufacturing step may be acceptable. Therefore, a defect tolerance may define acceptable limits for a particular manufacturing operation. In one embodiment, the defect tolerance is defect-specific. The situation may be that different types of defects can have different effects on device performance. For example, defects (such as increased edge roughness, pattern rounding, or the like) may generally be associated with reduced device performance (e.g., increased device resistance, increased residual capacitance, or the like), but may not Can cause catastrophic failure. These defects can be assigned a relatively high defect tolerance. In contrast, defects (such as unwanted bridges between structures (e.g., electrical connections), unwanted gaps between structures (e.g., missing electrical connections), or the like) can cause catastrophic failures and can It is therefore assigned a relatively low defect tolerance.

In another embodiment, the defect tolerance is pattern specific. For example, certain patterns may require more precise manufacturing requirements than other patterns, which may control relative defect tolerances.

It should be further recognized in this article that defects can be associated with various root causes. Therefore, the tolerance of the defect can be changed according to the root cause of the defect, so that a specific root cause can be identified and / or mitigated. For example, defects can be caused by fluctuations in components in a lithography system, such as (but not limited to) fluctuations in a sample stage of a fixed sample, fluctuations in the intensity and / or spectral content of an illumination source, and in lithography systems. Optical turbulence, vibration or the like associated with the generated heat. These root causes can be mitigated to some extent by choosing materials and system designs. By way of another example, random procedures (such as, but not limited to, photon shot noise) can introduce random (eg, arbitrary) defects even under idealized stable conditions. In addition, the universality of these random procedures can be inversely proportional to the illumination wavelength, so that the resulting defects can become more and more common as the illumination wavelength decreases. These root causes can represent more basic limitations of a particular system.

Regardless of the specific selected value or method of defect tolerance, the processing window indicates the lithographic configuration range that provides acceptable manufacturing. A separate processing window can therefore be determined for each pattern of interest (e.g., for a lithographic configuration range for which a particular pattern can be made) and for any selected group of patterns of interest (e.g., for which it can be made) One of all selected patterns lithographic configuration range).

In one embodiment, the method 200 includes a step 202 of receiving a pattern layout including a sample of a plurality of patterns fabricated with a selected lithographic configuration defining a processing window. For example, the sample may include a DOE sample containing a pattern of interest manufactured in a systematically varying lithographic configuration. The patterns of interest may include any type of pattern for which an accurate processing window is required, such as (but not limited to) an actual pattern fabricated on a specific layer of a semiconductor device, or designed to be sensitive to specific lithographic parameters Representative patterns (eg, focus and / or dose-dependent measurement target patterns).

In another embodiment, the pattern layout includes the location of the pattern of interest on the sample and the corresponding lithographic configuration used in manufacturing. In this regard, the pattern layout may operate as a lookup table for one of the patterns based on the pattern type, lithographic configuration, and / or position on the sample.

In another embodiment, the method 200 includes a step 204 of detecting a sample with a physical detection device (PID) (eg, PID 102) to generate a PID identification defect. In another embodiment, the method 200 includes a step 206 of verifying the PID identification defects with a defect verification device (DVD) (eg, DVD 106). As previously described herein, the PID and the DVD can be complementary systems, so that the PID can provide a relatively high-speed, low-resolution detection, and the DVD can provide a relatively low-speed, high-resolution detection . In this regard, PID can quickly identify possible defects that can be subsequently verified by DVD to determine if a defect is present.

PID may implement any defect identification technique known in the art for identifying possible defects on a pattern made on a sample. For example, the PID can compare a pattern made in a selected lithographic configuration with a reference to identify possible defects. The reference may further include, but is not limited to, one of the stored reference materials or a POI that is manufactured on the sample under a nominal lithographic condition and does not include manufacturing defects. In addition, the PID may sort and / or rank the identified possible defects for further analysis. Defect detection is usually described in U.S. Patent No. 7,877,722, titled "Systems and methods for creating inspection recipes" and issued January 25, 2011, and titled "Methods and systems for detecting defects in a reticle design pattern" and in Full text of all cases in US Patent No. 7,769,225 issued on August 3, 2010 and entitled "Methods and systems for detecting defects in a reticle design pattern" and issued on July 3, 2012 Incorporated herein. By way of another example, the PID can identify defects at least in part using design information such as, but not limited to, the designed geometry of the pattern, physical layout, material properties, or electrical properties. Defect detection using design data is generally described in U.S. Patent No. 7,676,077, titled `` Methods and systems for utilizing design data in combination with inspection data '', issued March 9, 2010, and entitled `` Computer-implemented methods for detecting and / or sorting defects in a design pattern of a reticle '' and U.S. Patent No. 7,729,529 issued on June 1, 2010 and titled `` Detecting defects on a wafer with run time use of design data '' and in 2015 In US Patent No. 9,183,624, issued on November 10, the entire text of all cases is incorporated herein by reference. The detection and ordering of defects in a design pattern is generally described in U.S. Patent No. 8,111,900, titled "Computer-implemented methods for detecting and / or sorting defects in a design pattern of a reticle" and issued on February 7, 2012. The full text of the case is incorporated herein by reference.

The situation may be that if the feature is smaller than the resolution of the PID, the PID may not be able to clearly resolve all the patterns of interest on the sample. However, the PID may still be able to identify possible defects on the same book. For example, comparing an image containing a pattern of a manufacturing defect with an image of a nominally defect-free pattern may provide an indication of the manufacturing defect, even though the defect may not be fully resolved.

In another embodiment, the PID provides one of the sample recordable physical measurements. The data generated from the PID may therefore be suitable for storage and subsequent analysis (e.g., by VID). For example, the PID may provide a composite image of a sample suitable for local storage on the PID or on a separate storage device such as, but not limited to, a server, a non-volatile storage drive, or the like. .

In another embodiment, a pattern of interest (e.g., a pattern on a DOE sample, for which a processing window is determined) is assigned a pattern trust value, which can be used as an indication of the ease of defects within the processing window. Operate with a good value for perceptual. For example, the pattern confidence value may indicate a degree of trust in a pattern-specific processing window known for a particular pattern within a selected accuracy. In addition, the pattern trust value can be improved or updated at any time when considering more information about the processing window.

Prior to detection by the PID in step 204, any confidence value may be assigned to the pattern of interest. In one embodiment, a common pattern trust value is assigned to all patterns of interest before PID detection. In this regard, no assumptions have been made regarding the susceptibility of any pattern to defects within the processing window defined by the DOE sample. In another embodiment, the pattern of interest is assigned a different pattern trust value before PID detection. The pre-detection pattern confidence level can incorporate any number of factors that can affect the expectation that a corresponding measurement will promote improved processing windows. For example, a pattern trust value may be assigned based on design information such as, but not limited to, information associated with physical size, shape, or orientation of the pattern, the material from which the pattern is made, the optical properties of the pattern, or the electrical properties of the pattern. In this regard, the known design characteristics of a pattern may provide a basis for assigning different patterns of trust levels to different patterns before performing any analysis or inspection. By way of another example, the pattern trust value may be assigned based on a program simulation, such as, but not limited to, an optical proximity correction (OPC) simulation.

In another embodiment, the pattern layout is mapped to the measurement area of the PID and / or DVD. The PID and / or DVD may include a predetermined measurement pattern for physical measurement of a sample. For example, the PID and / or DVD may measure the sample through a series of scanning strips, images, or the like associated with the movement of the illumination beam across the sample. Therefore, the pattern layout can map various manufacturing patterns and corresponding lithographic configurations to specific measurement areas (eg, scanning tape, image, field of view, or the like) of the PID and / or DVD.

FIG. 3A is a top view of a sample 118 (eg, a DOE sample or the like) for processing a window qualification test according to one or more embodiments of the present invention. In one embodiment, the sample 118 includes a plurality of grains 302 that include a pattern of interest fabricated in a varying lithographic configuration. The dies may have any configuration of patterns of interest suitable for processing window qualification. For example, each die 302 may include a set of common patterns of interest, so that different grains 302 can provide data for each pattern of interest according to different lithographic configurations. By way of another example, different dies 302 may include different patterns of interest. In addition, the die 302 may be disposed on the sample 118 in any suitable manner. In addition, the sample 118 may include reference grains fabricated in a nominal lithographic configuration (e.g., for those lithographic configurations that do not produce defects during manufacturing) scattered throughout the sample 118, so that the During the inspection, the die 302 manufactured with the changed lithographic configuration is compared with the reference die. In one example, the die 302 may be (but is not required to be) configured in groups of three, including a reference die manufactured in a nominal lithographic configuration and two tests manufactured in a selected lithographic configuration. Grain. In this regard, the two test grains can be directly compared to the reference grain during the inspection.

FIG. 3B is a top view illustrating a single die 302 of a plurality of scanning bands 304 of a scanning PID according to one or more embodiments of the present invention. In one embodiment, the PID physically interrogates the die 302 by scanning an illumination beam (e.g., an illumination beam 116 or the like) across the sample 118 in a series of scanning strips 304 and detecting radiation emitted from the sample 118. In addition, individual scanning strips 304 may be truncated at the edges of each die 302 (for example, as shown in FIG. 3B), extend beyond the edges of the die 302 (for example, into a scribe lane), or may span multiple die Granules 302 extend. It should be understood that the illustration of one of the scan PIDs in FIG. 3B is provided for illustration purposes only and should not be construed as limiting. As previously described herein, a PID may utilize any number of sample analysis techniques, such as (but not limited to) sequential imaging. In this regard, although not shown, each die 302 can be analyzed as a measurement region through a series of one or more images.

FIG. 3C is a top view illustrating a single scanning strip 304 of a plurality of fields of view 306 of a DVD (eg, DVD 106 or the like) according to one or more embodiments of the present invention. In one embodiment, the DVD has a field of view higher than a resolution of the PID but smaller than a field of the PID, so that a scanning zone 304 may include a plurality of fields of view 306 of the DVD. It should be noted that the field of view 306 of the DVD does not need to be aligned with a specific scanning zone 304 of the PID, as shown in FIG. 3C. For example, the field of view 306 may span two scanning bands 304 of the PID.

In another embodiment, each measurement area of the PID and / or DVD (for example, the scanning zone 304, the field of view 306, or the like) may be assigned a learning potential value, and the learning potential value may be used as an indication of a specific measurement area One of the tests operates by exposing defects and providing one of the desirable values of corresponding data suitable for improving the processing window. In this regard, the learning potential value can be operated as a priority metric, so that detection of a high-priority measurement area is expected to provide more information suitable for improving the processing window compared to a low-priority measurement area. In another embodiment, the measurement area of the PID and / or DVD is divided into smaller sub-units (e.g., sub-scanning bands, sub-images, sub-fields of view, or similar) in which each sub-unit can be assigned a separate learning potential value. By). Therefore, compared with the measurement area of a specific device, the learning potential value can be more subtle.

The learning potential value used to measure the area (e.g., scanning zone 304, field of view 306, or the like) may be based on any number of factors. For example, the learning potential value may be based on a pattern trust value of a pattern in each measurement area. In one example, the learning potential value may be derived as a statistical measure (eg, an average value, a median value, or the like) of one of the pattern trust values of the patterns in each measurement area. In another example, the learning potential value may be based on the diversity of patterns, so that a measurement area with a higher number of different patterns may have a higher learning potential value.

By another example, the learning potential value can be based on the deviation of the lithographic configuration from the nominal lithographic configuration. For example, the situation may (but is not required) is that a measurement area containing a pattern made with a lithographic configuration close to the nominal configuration is relatively less likely to be defective. The detection of these measurement areas may be less likely to result in the detection of a defect that would result in an improvement (e.g., narrowing) of the processing window. Therefore, a relatively low learning potential can be assigned to these measurement areas. Conversely, the situation may be (but is not required to be), and the measurement area including the pattern made with the lithographic configuration far exceeding the nominal configuration is relatively likely to be defective. The detection of these measurement areas may be more likely to lead to the detection of a defect that will lead to an improvement in the processing window. Therefore, a relatively high learning potential can be assigned to these measurement areas.

In addition, the learning potential value may be based on a weighted combination of one of factors such as, but not limited to, the number (or count) of one of the patterns, the diversity of the patterns, the pattern confidence value, or the lithographic configuration.

In another embodiment, the PID provides a recordable physical measurement of one of the entire samples for subsequent defect analysis, but only detects defects in a selected portion of one of the samples. It should be recognized in this article that defects identified by PID must usually be verified by DVD, which is a time-consuming process. Therefore, the situation may be that, for the processing window eligibility test, attempts to identify all defects on a DOE sample in a first pass and subsequently verify those identified defects in a first pass may be worse than in a first pass Testing the calibration portion of the sample over and over again, followed by subsequent repeated testing of the additional calibration portion of the sample, is as efficient. In this regard, one of the inspection recipes for the PID may include locating samples to detect defects generated based on the pattern layout.

In this regard, the PID may provide one first pass of the sample based on a selected portion of the sample, which may include (but is not limited to) a selected pattern, a selected lithographic configuration, and / or a selected measurement area of the sample. In addition, system resources (e.g., processing time, processing capacity, or the like) can efficiently identify defects in a selected portion of the sample by PID during the first pass, and can be recorded by using PID to analyze the sample Data (eg, one of the samples may record images or the like) may be provided for subsequent analysis.

The portion of the sample selected for the first pass detection by the PID can be selected based on various factors.

For example, a portion of a sample selected for first pass detection by the PID may be selected to provide a rough analysis of one of the processing windows. For example, a DOE sample may contain a large number of patterns made with relatively finely spaced variations of a lithographic configuration. The situation may be that the overall detection efficiency can be improved by first analyzing the pattern according to a coarse interval between the lithographic configurations, and then performing a more detailed analysis only in the calibration area. In this regard, a relatively small number of data points can be used in rough analysis to determine general trends. Subsequent analysis can then provide calibration detection at critical points based on rough measurements. Therefore, the detection time can be efficiently used.

By way of another example, the portion of the sample selected for the first pass analysis of the PID may be selected based on the learning potential value of the measurement area of the PID. For example, a selected number of measurements with a relatively high learning potential (e.g., providing a high expectation of data suitable for improving the processing window) may be selected for the first pass detection.

By way of another example, the portion of the sample selected for the first pass analysis by PID may be selected based on the physical distribution of the pattern across the DOE samples. The situation may be that a test sample may include a wide range of patterns that are physically dispersed throughout the sample using a varying lithographic configuration. Because PID is a physical instrument that generates data by physically interacting with a sample (e.g., via an illumination beam), at least in part, the portion of the sample selected for analysis with the first pass of the PID may be selected to include the physical entity. Samples grouped (e.g., within a common scanning zone, a common field of view, or the like).

By way of another example, the portion of the sample selected for the first pass analysis by PID may be selected based on the pre-selected region of interest. For example, design information may be used to identify patterns and / or areas of a sample as areas of interest for PID. In one example, specific patterns (eg, "weak" patterns) that are expected to be susceptible to changes in the lithographic configuration or specific patterns that are particularly important for the operation of a manufacturing device can be identified. In another example, specific areas of the wafer can be marked as defective (e.g., pits, scratches, or the like) prior to patterning, so that the surrounding patterns can be carefully analyzed (e.g., to determine the effect of the defect) Or reject surrounding patterns (for example, to avoid false information).

In another embodiment, the method 200 includes a step 208 of removing one or more lithographic configurations associated with the location of the PID-identified defect from the processing window. For example, PID identification defects may include possible defects identified by the PID in step 204 and subsequently verified by the DVD 106 in step 206. Therefore, step 208 may include improving (eg, narrowing) the initial processing window based on the presence of defects.

As previously described herein, the situation may be that for a given manufacturing step, a specific number and / or specific type of defects may be acceptable, which may be described by a defect tolerance. In this regard, step 208 may include identifying and removing a lithographic configuration that produces a defect on one or more patterns that violates the selected defect tolerance.

In another embodiment, the value of the pattern trust value and / or the learning potential value (eg, of PID and / or DVD) is updated after the processing window is improved. For example, the situation may be that removing a particular lithographic configuration from the processing window may change the expected susceptibility to making defective patterns in the improved processing window, which may be reflected by updating the pattern trust value. Similarly, the learning potential values of the measurement areas of the PID and / or DVD can be updated to reflect the increased knowledge of the processing window and the modified expectations of the probability that detecting a particular measurement area will result in further improvement of the processing window.

In another embodiment, method 200 includes iteratively improving the processing window by removing one or more lithographic configurations associated with a VID identification defect identified by analyzing selected portions of the stored PID data with VID. First step 210.

VID can detect any part of the data generated and / or stored by PID without moving the sample. In this regard, after the sample is detected in step 204 by the PID, the sample may be moved to a DVD for verification in step 206. The sample can then be held in the DVD for the duration of the process window qualification check to verify possible defects identified by the VID.

In addition, VID can access any part of the PID data corresponding to any desired part of the sample on demand. In this regard, the VID can detect any selected measurement area of the PID and / or DVD (e.g., scanning strip 304, field of view 306, or the like) without having to consider the physical location on the sample. In addition, the VID can detect sub-units (e.g., sub-scan bands, sub-images, sub-fields of view, or the like) of the measurement area. It should be recognized in this article that, instead of translating the sample to a desired position and then performing a measurement for analysis of similar tests on one of the PIDs, on-demand access to all parts of the sample tested with VIDs can be provided Significant efficiency benefits. Therefore, in cases where the sample is located in a DVD (for example, to verify a previously identified possible defect), iterative analysis of the sample with the PID will require repeated transfers of the sample between the DVD and the PID, which can introduce significant time delays and samples. May be risky.

In another embodiment, (e.g., by the controller 108 or the like), based on one of the expectations that the analysis will lead to an improvement in the detection and processing window for defects, a VID analysis and Selected part of stored PID data verified by DVD. In this regard, each iteration of step 210 includes analyzing (via the stored PID data) the calibration portion of the sample selected to optimize defect detection and avoid unnecessary data collection, so that the processing window can be determined efficiently with the desired accuracy .

For example, each iteration of step 210 may include analyzing a portion of a sample (eg, a measurement area, a subunit of a measurement area, or the like) having a pattern with a pattern trust value indicating a high probability of manufacturing a defect. So that the processing window can be improved efficiently. By way of another example, each iteration of step 210 may include analyzing a portion of a sample (eg, a measurement area, a subunit of a measurement area, or the like) having a learning potential value indicative of a high defect expectation, This makes it possible to efficiently improve the processing window.

In another embodiment, the pattern trust value and / or the learning potential value (eg, PID and / or DVD) are updated after the processing window is repeatedly improved by each step 210. For example, the situation may be that removing a particular lithographic configuration from the processing window may change the expected susceptibility to making defective patterns in the improved processing window, which may be reflected by updating the pattern trust value. Similarly, the learning potential values of the measurement areas of the PID and / or DVD can be updated to reflect the increased knowledge of the processing window and the modified expectations of the probability that detecting a particular measurement area will result in further improvement of the processing window.

In another embodiment, a selected portion of the stored PID data analyzed by VID and verified by DVD is dynamically changed in size in each iteration of step 210. In this regard, the size of the portions of the stored PID data analyzed in each iteration may be selected based on the expected results and is not limited to the limitations of a physical system. In addition, it should be recognized in this article that repeated analysis of a relatively small portion of the sample (e.g., subunits of the PID measurement area) with VID can promote "time slicing" of sample data and provide samples with high learning potential Efficient calibration of this area for rapid improvement of the processing window.

In another embodiment, the VID and DVD can be operated in parallel to further improve the efficiency of processing window qualification verification. For example, VID and DVD can be operated in an operation queue each, so that the failure time of each device can be minimized. For example, a controller (e.g., controller 108 or the like) may provide a recipe queue for the VID and / or DVD. In addition, the controller may interrupt and / or reconfigure the queued recipes for efficient operation as needed.

Any technique known in the art may be used to select selected portions of the stored PID data by VID analysis and verified by DVD in each iteration of step 210, such as (but not limited to) machine learning techniques or similar Neural networks (e.g., neural-like networks or the like).

In another embodiment, the method 200 includes a step 212 of providing a processing window when a selected end condition is met. For example, the processing window may be provided as an output to a control system for controlling a parameter of a lithography tool within the processing window.

The end condition may include any end condition that is applicable to the case where a processing window has been determined to be a desired specification. For example, the end condition may be based on the learning potential value of the measurement region across the sample (eg, the scanning zone 304, the field of view 306, or a portion thereof).

FIG. 4 is a graph 400 of a learning potential that changes over and over according to one or more embodiments of the present invention. For example, the graph 400 may indicate a learning potential of a specific measurement area or a statistical representation of a learning potential value across samples (eg, an average learning value or the like). As shown in FIG. 4, the situation may be that the learning potential value may decrease as the number of repetitions increases to indicate an increased accuracy and / or trust determination processing window.

In one embodiment, the ending condition includes a reduction to one or more learning potential values below a selected threshold. For example, the average (or a related statistical measure) of the learning potential across samples can be lowered below the selected threshold to indicate that the processing window has improved to the selected specification. In another embodiment, the ending condition includes that a rate of change (eg, a learning rate) of one of the learning potential values of the measurement area is reduced below a selected threshold.

In addition, some termination conditions may terminate iterations of step 210 for reasons other than the accuracy or reliance of the processing window. For example, the end condition may include a selected number of iterations, a selected processing time for one of the methods 200, an interrupt command from a user, or the like.

The subject matter described in this document sometimes illustrates different components contained within or connected to other components. It should be understood that these depicted architectures are merely exemplary and that many other architectures that implement the same functionality may be implemented in practice. In a conceptual sense, any configuration of components that achieve the same functionality is effectively "associated" so that the desired functionality is achieved. Therefore, any two components in this text that are combined to achieve a particular functionality may be considered to be "associated" with each other such that the desired functionality is achieved without considering the architecture or intermediate components. Similarly, any two components so related can also be considered to be "connected" or "coupled" to each other to achieve the desired functionality, and any two components that can be so connected can also be considered to be "coupled" to each other To achieve the desired functionality. Specific examples of coupling include (but are not limited to): entities that can interact and / or entities that interact, and / or components that can interact wirelessly and / or elements that interact wirelessly, and / or components that can interact logically and / or logic .

It is believed that the present invention and many of its attendant advantages will be understood from the foregoing description, and it will be understood that the form, construction, and configuration of the components can be made without departing from the disclosed subject matter or without sacrificing all of its substantial advantages Various changes. The forms described are merely illustrative and the intention is to cover and include such changes in the scope of the following patent applications. In addition, it should be understood that the present invention is only defined by the scope of the patent application accompanying the invention.

100‧‧‧hybrid detection system

102‧‧‧Entity Detection Device (PID)

104‧‧‧Virtual Inspection Device (VID)

106‧‧‧ Defect Verification Device (DVD)

108‧‧‧controller

110‧‧‧ processor

112‧‧‧Memory media / non-transitory memory media

114‧‧‧light source / Broadband Plasma (BBP) light source

116‧‧‧light beam / optical light beam / continuous light beam / pulse light beam / modulation light beam

118‧‧‧Sample

120‧‧‧ Lighting Path

122‧‧‧illumination path lens

124‧‧‧Optical components

126‧‧‧Sample stage

128‧‧‧ Detector / Particle Detector

130‧‧‧light path

132‧‧‧light path lens

134‧‧‧optical element

136‧‧‧Beam Splitter

138‧‧‧ Objective

200‧‧‧ Method

202‧‧‧step

204‧‧‧step

206‧‧‧step

208‧‧‧step

210‧‧‧ steps

212‧‧‧step

302‧‧‧ Grain

304‧‧‧Scanning tape

306‧‧‧field of view

400‧‧‧ graph

Those skilled in the art can better understand many advantages of the present invention by referring to the accompanying drawings, wherein: FIG. 1A is a conceptual diagram of a hybrid detection system according to one or more embodiments of the present invention. FIG. 1B is a conceptual diagram for scanning a focused optical illumination beam across a PID of a surface of a sample according to one or more embodiments of the present invention. FIG. 1C is a conceptual diagram for imaging and / or scanning a PID of a sample according to one or more embodiments of the present invention. FIG. 1D is a conceptual diagram of a PID configured as a particle beam detection system according to one or more embodiments of the present invention. FIG. 2 is a flowchart illustrating steps performed in a method for determining a processing window according to one or more embodiments of the present invention. FIG. 3A is a top view of a sample for processing a window qualification test according to one or more embodiments of the present invention. FIG. 3B is a top view illustrating a single die of a scanning band of a scanning PID according to one or more embodiments of the present invention. FIG. 3C is a top view illustrating a single scanning band of a plurality of fields of view of a DVD according to one or more embodiments of the present invention. FIG. 4 is a graph of a learning potential that changes over and over according to one or more embodiments of the present invention.

Claims (32)

An inspection system includes: a controller communicatively coupled to a physical inspection device (PID), a virtual inspection device (VID) configured to analyze stored PID data, and a defect verification device (DVD), The controller includes one or more processors that are configured to execute instructions, thereby causing the one or more processors to: receive a pattern layout of a sample, the sample includes defining a process A plurality of patterns made by the selected lithographic configuration of the window, the pattern layout correlates the positions of the plurality of patterns on the sample with the lithographic configuration of the processing window; receiving identification by analyzing the sample with the PID Position of the PID identification defect, wherein the PID identification defect is verified by the DVD; removing one or more lithographic configurations associated with the positions of the PID identification defect from the processing window; by Removing one or more lithographic configurations associated with a VID identification defect identified by analyzing selected portions of the stored PID data using the VID to iteratively improve the processing window; and Providing the output process window as a beam condition. The inspection system of claim 1, wherein the processing window is iteratively improved by removing one or more lithographic configurations associated with a VID identification defect identified by analyzing selected portions of the stored PID data with the VID. Including: selecting a part of the stored PID data analyzed with the VID; receiving the location of the VID identification defect identified by analyzing the selected part of the stored PID data with the VID, wherein the VID identification defects are verified by the DVD ; And removing one or more lithographic configurations associated with the VID identification defects from the processing window. If the inspection system of claim 1, wherein the VID identification defects are verified by the DVD. If the inspection system of claim 1, wherein the one or more processors are further configured to execute program instructions, the program instructions are configured to cause the one or more processors: assign a merit to instruct the processing The plurality of patterns of the plurality of lithographic configurations in the window, the plurality of patterns being defective for the plurality of lithographic configurations, wherein the stored PID data analyzed by the VID is selected based on the good values Those selected parts. The inspection system of claim 4, wherein the processing window is iteratively improved by removing one or more lithographic configurations associated with a VID identification defect identified by analyzing selected portions of the stored PID data with the VID. Including iterations: Selecting a portion of the stored PID data analyzed by the VID by maximizing the diversity of a pattern with a good value within a selected range within a selected specification; receiving the analysis by using the VID The location of the VID identification defect identified by storing the selected portion of the PID data, wherein the VID identification defect is verified by the DVD; and removing one or more micro-associations associated with the VID identification defect from the processing window Shadow configuration. The inspection system of claim 4, wherein the processing window is iteratively improved by removing one or more lithographic configurations associated with a VID identification defect identified by analyzing selected portions of the stored PID data with the VID. Including iteratively: selecting a part of the stored PID data analyzed by the VID by maximizing a number of patterns having a good value within a selected range within a selected specification; receiving the PID data stored by using the VID analysis The location of the VID identification defect identified by the selected portion, wherein the VID identification defect is verified by the DVD; and removing one or more lithographic configurations associated with the VID identification defect from the processing window . If the inspection system of claim 4, wherein the one or more processors are further configured to execute program instructions, the program instructions are configured to cause the one or more processors: based on the removal from the processing window The VIDs identify defects and update the merit values. The inspection system of claim 4, wherein the one or more processors are further configured to execute instructions, thereby causing the one or more processors to: cause the plurality of patterns and analyze one of the samples using the PID. One or more scan bands are related; and assigning a learning potential value to the one or more scan bands based on the merit of the plurality of patterns within the one or more scan bands, wherein based on the one or more scan bands The learning potential values of the bands are scanned to select the selected portions of the stored PID data analyzed by the VID. The detection system of claim 8, wherein the learning potential values indicate at least one of a pattern having a variety of merit that satisfies a selected criterion or a pattern having a merit that satisfies the selected criterion. The inspection system of claim 8, wherein the learning potential values of the one or more scanning zones indicate that the one or more scanning zones contain a predicted probability of a manufacturing defect. The inspection system of claim 8, wherein the processing window is iteratively improved by removing one or more lithographic configurations associated with a VID identification defect identified by analyzing selected portions of the stored PID data with the VID. Including iteratively: selecting at least a portion of a scan zone of the stored PID data selected for analysis with the VID based on the learning potential; receiving a VID identification defect identified by analyzing the selected portion of the scan zone of the stored PID data with the VID Position, wherein the VID identification defects are verified by the DVD; and one or more lithographic configurations associated with the VID identification defects are removed from the processing window. The detection system of claim 8, wherein the iteration further includes: updating the learning potential value of the selected scan zone based on the VID identification defect. The detection system of claim 12, wherein updating the learning potential value of the selected scanning zone based on the VID identification defect includes: decreasing the learning potential value of the selected scanning zone. The detection system of claim 13, wherein the selected end condition includes: the one or more scan bands have a learning potential value below a selected threshold. The inspection system of claim 4, wherein the one or more processors are further configured to execute instructions, thereby causing the one or more processors to: correlate the plurality of patterns with one or more fields of view of the DVD ; And assigning a learning potential value to the one or more fields of view based on the merit of the plurality of patterns in the one or more fields of view, wherein the learning based on the one or more fields of view Potential value to select those selected parts of the stored PID data analyzed by the VID. The detection system of claim 15, wherein the learning potential values indicate at least one of a pattern having a variety of merit that satisfies a selected criterion or a pattern having a merit that satisfies the selected criterion. The inspection system of claim 15, wherein the learning potential values of the one or more fields of view indicate a predicted probability that the one or more fields of view contain a manufacturing defect. The inspection system of claim 15, wherein the processing window is iteratively improved by removing one or more lithographic configurations associated with a VID identification defect identified by analyzing selected portions of the stored PID data with the VID. Including iteratively: using the VID to select at least one field of view of the one or more fields of view based on the learning potential; receiving the location of a defect identified by the VID identified by analyzing the selected at least one field of view with the VID, wherein the The VID identification defect is verified by the DVD; and one or more lithographic configurations associated with the VID identification defect are removed from the processing window. The detection system of claim 15, wherein the iteration further comprises: updating the learning potential value of the at least one selected field of view based on the VID identification defects. If the detection system of claim 19, wherein updating the learning potential value of the at least one selected field of view based on the VID identification defect comprises: decreasing the learning potential value of the at least one selected field of view. The detection system of claim 20, wherein the selected end condition includes: the one or more fields of view have a learning potential value below a selected threshold. If the detection system of item 1 is requested, the selected end condition includes: a selected number of iterations. If the detection system of item 1 is requested, the selected end condition includes: a selected running time. The detection system of claim 1, wherein the PID includes: at least one of an optical detection system or an electron beam detection system. The inspection system of claim 1, wherein the DVD includes: at least one of a viewing scanning electron microscope, a critical size scanning electron microscope, or a detection scanning electron microscope. An inspection system includes: a physical inspection device (PID); a virtual inspection device (VID) configured to analyze stored PID data; a defect verification device (DVD); and a controller that communicates with Coupled to the PID, the VID, and the DVD, the controller includes one or more processors that are configured to execute instructions, thereby causing the one or more processors to: A pattern layout including a plurality of patterns made with a selected lithographic configuration defining a processing window, the pattern layout relating the positions of the plurality of patterns on the sample to the lithographic configuration of the processing window ; Receiving the locations of PID identification defects identified by analyzing the sample with the PID, wherein the PID identification defects are verified by the DVD; removing from the processing window associated with the locations of the PID identification defects One or more lithographic configurations; iteratively modified by removing one or more lithographic configurations associated with a VID identification defect identified by analyzing selected portions of the stored PID data with the VID The processing window; and to meet the process window to provide a selected output as a termination condition. A detection method includes: receiving a pattern layout of a sample, the sample including a plurality of patterns manufactured using a selected lithographic configuration defining a processing window, the pattern layout bringing the positions of the plurality of patterns on the sample and The lithographic configuration of the processing window is related; detecting the sample with a physical detection device (PID) to generate PID identification defects; verifying the PID identification defects with a defect verification device (DVD); removing from the processing window One or more lithographic configurations associated with the locations of the PID identification defects; by removing one or more of the VID identification defects associated with the selected portion of the PID data stored by analyzing the PID identification The lithographic configuration repeatedly improves the processing window; and provides the processing window as an output when a selected end condition is met. The detection method of claim 27, wherein the processing window is repeatedly improved, one of which includes: selecting a portion of the stored PID data analyzed by a virtual detection device (VID) configured to analyze one of the stored PID data; receiving The location of the VID identification defect identified by analyzing the selected portion of the stored PID data with the VID, wherein the VID identification defect is verified by the DVD; and removing from the processing window associated with the VID identification defect One or more lithographic configurations. The detection method of claim 27, further comprising: assigning a figure of merit to the plurality of patterns indicating a plurality of lithographic configurations in the processing window, the plurality of patterns being manufactured for the plurality of lithographic configurations Defects, where the part of the stored PID data that is selected for analysis with the VID includes: based on the merit, the part of the stored PID data that is selected for analysis with the VID. If the inspection method of claim 29, wherein the portion of the stored PID data selected for analysis with the VID based on the merit values includes: selecting the portion of the stored PID data to include the processing window associated with the manufacturing defect The selected number of patterns in the selected number of lithographic configurations. If the inspection method of claim 29, wherein the portion of the stored PID data selected for analysis with the VID based on the merit values includes: selecting the portion of the stored PID data to include the processing window associated with the manufacturing defect One of the plurality of patterns of the selected number of lithographic configurations is selected from a plurality of patterns. The detection method of claim 29, wherein the iteration further comprises: updating the figure of merit based on the VID identification defects removed from the processing window.